Our dataset, VANiLLa (Verbalized Answers in Natural Language at Large scale) consists of simple questions \(Q_{NL}\) , selected from the CSQA [1]} and SimpleQuestionsWikidata [2]} datasets and answers \(A_R\) , labels fetched from the Wikidata [3]} Knowledge Graph, along with their answers in natural language \(A_V\) , generated using Amazon Mechanical Turk (AMT). We adapt our dataset from conventional Question Answering over Knowledge Graph (KGQA) datasets on Wikidata for the purpose of offering the possibility of extending them with verbalizations. The dataset creation process workflow uses a semi-automatic framework, as described in Figure
 REF , consists of four stages: [(i)]
